PC Magazine July 2017

Makoto Koike is a cucumber farmer in Japan.
He’s a former embedded systems designer
who spent years working in the Japanese
automobile industry, but in 2015 he returned home to
help out on his parents’ farm. He soon realized that the
manual task of sorting cucumbers by color, shape, size,
and attributes such as “thorniness” was often trickier
and more arduous than growing them. Inspired by the
deep learning innovation of Google’s artificial
intelligence (AI) software AlphaGo, he set out to
automate the task.
Businesses are beginning to implement practical AI in
all sorts of ways, but it’s safe to say that no one saw
Koike’s cucumber-sorting solution coming. Koike had
never worked with AI techniques before, but using the
open-source TensorFlow machine learning (ML)
library, he started inputting images of cucumbers.
Thanks to computer vision algorithms for recognizing
objects and deep learning to train TensorFlow on the
nuances of cucumbers, Koike realized it could identify
and sort the vegetables with a high level of accuracy.
Then, by using nothing but TensorFlow and a cheap
Raspberry Pi 3 computer, Koike built his automated
sorting machine, which the farm still uses today.
Using the
open-source
TensorFlow
machine learning
(ML) library,
he started
inputting
images of
cucumbers.
Makoto Koike’s
cucumber-sorting
machine makes use
of computer vision
algorithms and
deep learning to
identify and sort the
vegetables.